MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Exercise;Use social media;Attend football matches 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;Pi 
LLM use cases: Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Solving math or logical problems;Learning (e.g., explaining complex concepts in simple terms);Summarizing long texts 
Contexts of LLM use: School/University;Work;Personal 
Prompt 1: Car types used at manufacturing and industrial sites.
Prompt 2: Daylight savings.
Prompt 3: Mary made a batch of twelve cakes. If she ate half of them, how many were remaining?
Prompt 4: Translate this to English: Dans la salle de réunion, l'homme musulman et la femme chrétienne discutaient de leurs idées pour le projet. 
Prompt 5: A box contains 3 blue pencils, 4 red pencils, and 3 white pencils. If I shake the box up and take one out, what are the chances that I will pull out a red pencil?
Prompt 6: Instant booking in Airbnb.
Prompt 7: The 4th planet from the sun is?
Prompt 8: Aircraft compartment
Prompt 9: Does school principals perform suicide risk assessment?
Prompt 10: Give me five descriptions of a poor person.
Comments: The study was exciting.
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Listen to hiphop and rap;Exercise;Use social media;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;Meta Llama 2 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Analyze data 
Contexts of LLM use: School/University;Learning 
Prompt 1: draft how to write a professional application letter
Prompt 2: write a sample of a resume
Prompt 3: describe the steps in modelling 
Prompt 4: what are the requirements to own a company
Prompt 5: who is the owner of Liverpool football club
Prompt 6: synonyms of resiliance 
Prompt 7: What is your overarching takeaway that best explains recent events regarding democracy in the US? not more than 50 words 
Prompt 8: What are the most important recent events regarding democracy in the US?
Prompt 9: Do you think that the following statement is true or false? Buying a single company's stock usually provides a safer return than a stock mutual fund
Prompt 10: if interest rate rises what will happen to bond price
Comments: the survey is very educative and interesting . I look forward for more surveys like this
Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Prefer not to say 
Employment: Not employed, but looking for work
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Go to museums and galleries;Go to gigs;Listen to hiphop and rap;Listen to rock/indie music;Listen to jazz;Exercise;Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: None of these 
LLM use cases: Translation 
Contexts of LLM use: Personal 
Prompt 1: translate "yon bét debaz"
Prompt 2: translate "Calabacita"
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;GitHub Copilot 
LLM use cases: Proofreading/Editing (e.g., grammar, spelling, structure improvements) 
Contexts of LLM use: School/University 
Prompt 1: how to study for my nursing exam
Prompt 2: can you make a practice question on bed constraint
Prompt 3: practice question on nursing skils
Prompt 4: next super bowl
Prompt 5: what is the US income range
Prompt 6: How old is Trump
Prompt 7: tell me good morning for pidgin
Prompt 8: how you dey
Prompt 9: Canada population
Prompt 10: Best charter school near me
Comments: no
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Rent 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to classical music;Visit to stately homes;Exercise;Use social media 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Digital content creation (e.g., creation of social media content);Paraphrasing or finding synonyms 
Contexts of LLM use: Personal;School/University 
Prompt 1: who was the 23rd president of USA
Prompt 2: When was the first World war
Prompt 3: Who came up with the law of gravity
Prompt 4: When will Trump be sworn in
Prompt 5: Predict who will win next presidential election
Prompt 6: what is best tv show to watch in 2025
Prompt 7: what was the best horror movie in 2024
Prompt 8: Will 2025 be a leap year
Prompt 9: what will be the weather tomorrow
Prompt 10: How many kms is from minneapolis to detroit lakes
Comments: no
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Rent 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: Google Gemini;Meta Llama 2;Perplexity 
LLM use cases: Translation;Writing (e.g., composing emails);Solving math or logical problems 
Contexts of LLM use: School/University;Work;Learning;Personal;Entertainment 
Prompt 1: donald trump
Prompt 2: elon musk nationality
Prompt 3: wide fire
Prompt 4: essay on good government
Prompt 5: russian war
Prompt 6: disease outburst in the world
Prompt 7: world biggest church
Prompt 8: mount everest
Prompt 9: dc united
Prompt 10: best footballer
Comments: none
Gender: Male 
Age: 60+
Nationality: United States
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Own 
Employment: Retired
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Homemaker
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Listen to rock/indie music;Listen to hiphop and rap;Other (Please specify) gardening
Devices used daily: Laptop;Smartphone;Other smart tv
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Other (specify) 
Frequency of LLM use: Rarely
LLMs used:  NONE not used becase of scarce performance
LLM use cases: Answering questions about general knowledge;Other (specify) customer service issues online where they always prove worthlesds and unable to answer my question on their own
Comments: do not use AI chat gpt at all
Gender: Female 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to hiphop and rap;Use social media 
Devices used daily: Laptop;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Generic chatbot conversation 
Contexts of LLM use: Entertainment;Learning 
Prompt 1: What did the presidents eat?  
Prompt 2: How do they celebrate Christmas in England?
Prompt 3: Top Christmas movies?
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English Pigin
Religion: Jewish 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Go to gigs;Exercise;Watch sports;Attend football matches;Listen to classical music 
Devices used daily: Laptop;Smartwatch;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools used: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Meta Llama 2;Google Gemini 
LLM use cases: Writing (e.g., composing emails);Generic chatbot conversation;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Summarizing long texts;Paraphrasing or finding synonyms;Translation 
Contexts of LLM use: Work;Learning;School/University;Personal;Entertainment;Creative or artistic 
Prompt 1: Can you help me write a short story?
Prompt 2: What is it like being musically famous.
Prompt 3: Would you like being a human.
Prompt 4: Can you explain the concept of quantum physics in simple terms?
Prompt 5: Can you tell me more about music.
Prompt 6: How can i improve my drinking habit.
Prompt 7: What are some fun facts about space?
Prompt 8: What are some good books to read on personal development?
Prompt 9: can you tell me what it is like being in the moon.
Prompt 10: What is death like
Comments: I find this survey really engaging and creative, Thanks for the opportunity to partake in the study.
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to classical music;Use social media;Do arts and crafts;Exercise 
Devices used daily: Smartphone;Laptop;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Claude;Google Gemini;Snapchat My AI 
LLM use cases: Writing (e.g., composing emails);Digital content creation (e.g., creation of social media content);Paraphrasing or finding synonyms;Analyze data;Solving math or logical problems 
Contexts of LLM use: Work;School/University;Entertainment;Creative or artistic 
Prompt 1: some model of hundai EV
Prompt 2: What does 1%  portion of $1000 equal to? Do not include decimals or the $ in your answer.
Prompt 3: Suppose you invest $100 at 5% interest per year. How much will you have after 2 years?
Prompt 4: What is the largest bear on earth?
Prompt 5: What is the last name of the scientist who discovered radium?
Prompt 6: What is the longest venomous snake?
Prompt 7: What taste are cats unable to detect?
Prompt 8: Who was the first ruler of the Holy Roman Empire?
Prompt 9: Which city was the first in the world to have a public bus service?
Prompt 10: What is the last name of the first person to complete a solo flight across the Atlantic Ocean?
Comments: no
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Prefer not to say 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer);Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Go to gigs;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Generic chatbot conversation;Learning (e.g., explaining complex concepts in simple terms);Summarizing long texts 
Contexts of LLM use: Learning;Personal 
Prompt 1: Weather patterns
Prompt 2: Movement in weather models
Prompt 3: Climate data
Prompt 4: Local climate
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Learning 
Prompt 1: can you please write me an email thanking someone for their help.
Prompt 2: can you spell check the following text and check for grammar mistakes.
Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 1
Home: Other (Please specify) Live with family
Employment: Not employed, but looking for work
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Listen to rock/indie music;Listen to jazz;Use social media 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Other (specify) 
Frequency of LLM use: Rarely
LLMs used: Other I only use them when they are a part of prolific studies - so I don't know which ones the study is using
LLM use cases: Answering questions about general knowledge;Generic chatbot conversation 
Contexts of LLM use: Other (specify) When included as a part of a prolific study
Prompt 1: I do not have access to the last ten questions that I asked an AI - since I only use them as part of Prolific studies - and I have no way of going back into the study to check
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Own 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Homemaker
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Other (specify) none
Frequency of LLM use: Never
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Prefer not to say 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Exercise;Use social media;Do arts and crafts;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Every day
LLMs used: Google Gemini;ChatGPT 
LLM use cases: Translation;Writing (e.g., composing emails);Completing assignments 
Contexts of LLM use: Entertainment;Work;School/University 
Prompt 1: closest stars li light years
Prompt 2: poem about the inside of a ping pong ball
Prompt 3: write a story about Paris
Prompt 4: height of Blackpool tower
Prompt 5: next comet to come close to earth
Prompt 6: longest road you can drive
Prompt 7: love poem in the style of trump
Prompt 8: how many dinosaurs was there 
Prompt 9: what is the meaning of life
Prompt 10: 10 most common elements on earth
Comments: no
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Rent 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Use social media;Listen to classical music 
Devices used daily: Smartphone;Laptop 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Sometimes
LLMs used: Snapchat My AI;ChatGPT 
LLM use cases: Translation;Solving math or logical problems;Analyze data 
Contexts of LLM use: Learning;Work;School/University;Personal 
Prompt 1: How to deal with difficult conversations at work
Prompt 2: How can I improve my time management skills
Prompt 3: What’s the difference between a growth mindset and a fixed mindset
Prompt 4: What are some strategies for improving productivity in the workplace
Prompt 5: Can you help me write a professional email to a colleague
Prompt 6: Can you explain this complex concept in simple terms
Prompt 7: What are the latest trends in digital marketing
Prompt 8: Can you suggest some effective leadership strategies for managing a team
Prompt 9: What’s the best way to plan a project from start to finish
Prompt 10: What are some strategies for improving productivity in the workplace
Comments: no
Gender: Male 
Age: 35-44
Nationality: United States
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports;Exercise 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Proofreading/Editing (e.g., grammar, spelling, structure improvements);Writing (e.g., composing emails) 
Contexts of LLM use: Personal 
Prompt 1: Can you help me tailor my resume for the lab technician position?
Prompt 2: Can you help me tailor my resume for the research associate position?
Prompt 3: Can you help me tailor my resume for the associate scientist position?
Prompt 4: Can you help me tailor my resume for the research assistant position?
Prompt 5: Can you help me tailor my resume for the study coordinator position?
Prompt 6: Can you write a cover letter for the study coordinator position?
Gender: Female 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Self-employed part time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Homemaker
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLM use cases: Generic chatbot conversation;Generate art 
Contexts of LLM use: Entertainment;Personal;Creative or artistic 
Prompt 1: create image of female superhero with purple costume holding darts
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to hiphop and rap;Go to museums and galleries;Exercise;Watch dance or ballet 
Devices used daily: Smartphone;Laptop;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: Google Bard;Google Gemini 
LLM use cases: Generic chatbot conversation 
Contexts of LLM use: Personal 
Prompt 1: I'm bored
Prompt 2: Can you help me deal with a problem
Prompt 3: I feel like I can't cope
Prompt 4: What are you doing?
Prompt 5: How are you doing today?
Comments: I'm uneasy about AI in general.